The authors also showed that using the training data as a knowledge base outperforms using them for training. This approach was built on the work of [1]} which, however, does not use the state-of-the-art Transformer-based language model but an RNN-based one. Furthermore, they use the inner product (IP) for similarity instead of the \(L^2\)  distance.
